In the present study, an artificial neural network known as feed-forward is used to analyze
the ability of the network to correctly classify the types of modulation Binary Phase Shift
Keying, Quadrature Phase Shift Keying and 16 Quadrature Amplitude Modulation. We
will use measured signals as inputs and targets of the network. Several scenarios have
been tested to verify their effectiveness, in this case is the capacity of correclty classify
the used modulation, since we have multiple parameters to be passed to the application
that will build the network. The tests have shown that, for this network, specifically, the
best classification is done in pairs. In the classification using all modulations, we have an
efficiency of 66,7% against 100% of the classification in pairs.